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This paper presents a text query-based method for keyword spotting from online Chinese handwritten documents. The similarity between a text word and handwriting is obtained by combining the character similiarity scores given by a character classifier. To overcome the ambiguity of character segmentation, multiple
KSORD (keyword search over relational database) techniques allow users to obtain information from databases, which is just like using search engines. However, the advanced techniques only realize exact queries, but not for fuzzy queries. The Rocchio algorithm of learning classification is introduced which is made a
Keyword-Driven Analytical Processing (KDAP) integrates the simplicity of keyword search with the aggregation power in OLAP (Online-Analytical Processing), which provides an easy-to-use solution to organize the data in a way that a business analyst needs for thinking about the data. For any user query, the system
In this paper we propose an approach for Chinese question analysis and answer extraction. A general question analysis process contains keyword extraction and question classification. Question classification plays a crucial role in automatic question answering. To implement the question classification, we have carried
A natural language information retrieval system ranks related documents according to criteria based on user query keywords and document similarities. However, many efforts have been made to make more useful query keywords because users do not use many keywords in their natural language search query when retrieving
to search and retrieve components. Proposed technique helps re-user to identify and retrieve software component. In its first step it matches keywords, their synonyms and their interrelationships. And then makes use of ant colony optimization, a probabilistic approach to generate rule for matching the component against
This work identifies relevant songs from a user's personal music collection to accompany pictures of an event. The event's pictures are analyzed to extract aggregated semantic concepts in a variety of dimensions, including scene type, geospatial information, and event type, along with user-provided keywords. These
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